APPLICATIONS AND STATISTICS FOR MULTIPLE HIGH-SCORING SEGMENTS IN MOLECULAR SEQUENCES
APPLICATIONS AND STATISTICS FOR MULTIPLE HIGH-SCORING SEGMENTS IN MOLECULAR SEQUENCES
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DOI：
10.1073/pnas.90.12.5873
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发表时间：
1993-06-15
影响因子：
11.1
通讯作者：
ALTSCHUL, SF
中科院分区：
文献类型：
--
作者：
KARLIN, S;ALTSCHUL, SF
基于分数的分子序列特征测量为蛋白质和DNA的研究提供了多种帮助。它们被许多序列数据库搜索程序所使用，也用于识别单个序列的独特属性。对于任何这样的测量，重要的是要知道什么是完全偶然发生的。高分段的统计分布已经在其他地方描述过了。然而，分子序列往往会产生一些高分片段，一些联合评估是有序的。本文描述了多个高分片段得分之和的统计分布，并举例说明了其在鉴别可能的跨膜片段和评价序列相似性方面的应用。
Score-based measures of molecular-sequence features provide versatile aids for the study of proteins and DNA. They are used by many sequence data base search programs, as well as for identifying distinctive properties of single sequences. For any such measure, it is important to know what can be expected to occur purely by chance. The statistical distribution of high-scoring segments has been described elsewhere. However, molecular sequences will frequently yield several high-scoring segments for which some combined assessment is in order. This paper describes the statistical distribution for the sum of the scores of multiple high-scoring segments and illustrates its application to the identification of possible transmembrane segments and the evaluation of sequence similarity.